Ashwini Patil
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Disordered domains and high surface charge confer hubs with the ability to interact with multiple proteins in interaction networks
A Patil, H Nakamura
FEBS letters 580 (8), 2041-2045, 2006
Hub promiscuity in protein-protein interaction networks
A Patil, K Kinoshita, H Nakamura
International journal of molecular sciences 11 (4), 1930-1943, 2010
Filtering high-throughput protein-protein interaction data using a combination of genomic features
A Patil, H Nakamura
BMC bioinformatics 6 (1), 100, 2005
HitPredict: a database of quality assessed protein–protein interactions in nine species
A Patil, K Nakai, H Nakamura
Nucleic acids research 39 (suppl 1), D744-D749, 2011
HitPredict version 4: comprehensive reliability scoring of physical protein–protein interactions from more than 100 species
Y López, K Nakai, A Patil
Database 2015, bav117, 2015
Organism-level analysis of vaccination reveals networks of protection across tissues
M Kadoki, A Patil, CC Thaiss, DJ Brooks, S Pandey, D Deep, D Alvarez, ...
Cell 171 (2), 398-413. e21, 2017
Methods for protein complex prediction and their contributions towards understanding the organization, function and dynamics of complexes
S Srihari, CH Yong, A Patil, L Wong
FEBS Letters, 2015
Domain distribution and intrinsic disorder in hubs in the human protein–protein interaction network
A Patil, K Kinoshita, H Nakamura
Protein Science 19 (8), 1461-1468, 2010
OPAL: prediction of MoRF regions in intrinsically disordered protein sequences
R Sharma, G Raicar, T Tsunoda, A Patil, A Sharma
Bioinformatics 34 (11), 1850-1858, 2018
Computerized polymorphic marker identification: experimental validation and a predicted human polymorphism catalog
JW Fondon III, GM Mele, RI Brezinschek, D Cummings, A Pande, J Wren, ...
Proceedings of the National Academy of Sciences 95 (13), 7514-7519, 1998
Sequence-and species-dependence of proteasomal processivity
DA Kraut, E Israeli, EK Schrader, A Patil, K Nakai, D Nanavati, T Inobe, ...
ACS chemical biology 7 (8), 1444-1453, 2012
MoRFPred-plus: computational identification of MoRFs in protein sequences using physicochemical properties and HMM profiles
R Sharma, M Bayarjargal, T Tsunoda, A Patil, A Sharma
Journal of Theoretical Biology 437, 9-16, 2018
Chemical composition is maintained in poorly conserved intrinsically disordered regions and suggests a means for their classification
HA Moesa, S Wakabayashi, K Nakai, A Patil
Mol. BioSyst. 8 (12), 3262-3273, 2012
OPAL+: length‐specific MoRF prediction in intrinsically disordered protein sequences
R Sharma, A Sharma, G Raicar, T Tsunoda, A Patil
Proteomics 19 (6), 1800058, 2019
HINT-a database of annotated protein-protein interactions and their homologs
A Patil, H Nakamura
Biophysics 1, 21-24, 2005
Predicting MoRFs in protein sequences using HMM profiles
R Sharma, S Kumar, T Tsunoda, A Patil, A Sharma
BMC bioinformatics 17 (19), 251-258, 2016
Linking transcriptional changes over time in stimulated dendritic cells to identify gene networks activated during the innate immune response
A Patil, Y Kumagai, K Liang, Y Suzuki, K Nakai
PLoS computational biology 9 (11), e1003323, 2013
Use of transcriptional synergy to augment sensitivity of a splicing reporter assay
N Levinson, R Hinman, A Patil, CRJ Stephenson, S Werner, GHC Woo, ...
RNA 12 (5), 925-930, 2006
Evaluation of Sequence Features from Intrinsically Disordered Regions for the Estimation of Protein Function
A Sharma, A Dehzangi, J Lyons, S Imoto, S Miyano, K Nakai, A Patil
PloS one 9 (2), e89890, 2014
FEATS: feature selection-based clustering of single-cell RNA-seq data
E Vans, A Patil, A Sharma
Briefings in Bioinformatics 22 (4), bbaa306, 2021
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